ABSTRACT: The trend towards generating and analyzing ever increasing data is leading to changes in the computing paradigm. Traditional compute centric model, where data is moved to location where computation is performed is no longer scaling with today’s large amount of machine generated data. In contrast a data-centric model, where data lives and is processed in different levels of storage hierarchy is becoming more desirable. Near Data Processing is not a new concept, however explosion of data caused by advances in Artificial Intelligence, IOT, health sciences and data analytics, etc. as well as innovations in memory and storage technologies are providing new opportunities and challenges for processing data in or close to where it resides. In this talk we will discuss these advancements. BIO: Anahita Shayesteh is a senior system architect and researcher at Samsung Memory Platform Lab in San Jose, California. She works on storage solutions for datacenter applications, leveraging new technologies in flash and SSD design. Anahita is a UCLA alumni who received her PhD in Computer Architecture in 2006 under Prof. Reinman. Prior to Samsung she was a research scientist at Intel Labs where she worked on various topics in architecture including CPU, GPU, Cache and Interconnect design. BIO: Rajiv Dhawan received his Bachelor of Science degree from Simon Fraser University in suburban Vancouver. He then moved on to get his Ph.D. from McGill University in Montreal, Quebec followed by a postdoctoral appointment at Stanford University. Rajiv started his career at DuPont Central Research & Development and joined Samsung Semiconductor in 2016 and is currently Director of Strategic Planning and Business Development. In this role, he manages University Relations for Device Solutions America and key activities include collaboration management, technology scouting and Ph.D. recruiting.